Assessing the effectiveness of surrogates for conserving biodiversity in the Port Stephens-Great Lakes Marine Park

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1 Assessing the effectiveness of surrogates for conserving biodiversity in the Port Stephens-Great Lakes Marine Park Vanessa Owen B Env Sc, B Sc (Hons) School of the Environment University of Technology Sydney Submitted in fulfilment for the requirements of the degree of Doctor of Philosophy September 2015

2 Certificate of Original Authorship I certify that the work in this thesis has not been previously submitted for a degree nor has it been submitted as part of requirements for a degree except as fully acknowledged within the text. I also certify that the thesis has been written by me. Any help that I have received in my research work and preparation of the thesis itself has been acknowledged. In addition, I certify that all information sources and literature used as indicated in the thesis. Signature of Student: Date: Page ii

3 Acknowledgements I thank my supervisor William Gladstone for invaluable support, advice, technical reviews, patience and understanding. I thank my family for their encouragement and support, particularly my mum who is a wonderful role model. I hope that my children too are inspired to dream big and work hard. This study was conducted with the support of the University of Newcastle, the University of Technology Sydney, University of Sydney, NSW Office of the Environment and Heritage (formerly Department of Environment Climate Change and Water), Marine Park Authority NSW, NSW Department of Primary Industries (Fisheries) and the Integrated Marine Observing System (IMOS) program funded through the Department of Industry, Climate Change, Science, Education, Research and Tertiary Education. The sessile benthic assemblage fieldwork was led by Dr Oscar Pizarro and undertaken by the University of Sydney s Australian Centre for Field Robotics. Dr Alan Jordan, NSW Office of the Environment and Heritage, provided assistance in coordinating fieldwork and developing the experimental design. Dr Nicole Hill, University of Tasmania Institute of Marine and Antarctic Studies provided their identification guides, and methods for processing and scoring autonomous underwater vehicle (AUV) digital imagery from South Eastern Tasmania, which assisted in the development of methods to assess AUV digital imagery from Port Stephens for this study. Coral Point Count with Excel extensions, developed by the National Coral Reef Institute, was used to determine cover of sessile benthic images. Professor Marti Anderson, University of Auckland, provided advice on methods for statistical analyses for the sessile benthic assemblage data set. Reef fish surveys were conducted as part of monitoring of fish assemblages within Port Stephens-Great Lakes Marine Park, undertaken by NSW Department of Primary Industries staff. I am grateful for assistance from Dr David Harasti, NSW Department of Primary Industries, for coordinating and undertaking fieldwork, and assistance with identification. I am grateful to Trent Alexander, Guy Graham and Steve Lindfield for assistance with fish survey fieldwork, and Tresa Morton (GIS Technician) for developing figures used in this thesis. Page iii

4 Table of Contents Chapter 1 Overview of Thesis Overall Aim Study Approach... 2 Chapter 2 Literature Review Patterns and Processes in Australian Temperate Marine and Estuarine Habitats Factors Influencing Marine and Estuarine Habitats and Assemblages The Need and Framework for Marine Protected Areas Effects of Marine Protected Areas Selection and Design of Marine Protected Areas The Need for, and Use of, Biodiversity Surrogates in the Selection and Design of Marine Protected Areas Conclusions Chapter 3 Study Area Chapter 4 Intra-habitat variability in biodiversity of temperate rocky reefs and its implications for the development of surrogates for conservation planning Introduction Methods Results Discussion Chapter 5 Scales of spatial autocorrelation in sessile benthic assemblages of subtidal rocky reefs and implications for marine protected area planning Introduction Page iv

5 5.2 Methods Results Discussion Chapter 6 Sources of variation in the biodiversity of rocky reef fishes and the implications for surrogacy schemes for conservation planning Introduction Methods Results Discussion Chapter 7 Sources of variation in the biodiversity of rocky reef fishes and the implications for surrogacy schemes for conservation planning: the influence of biogenic attributes of habitats Introduction Methods Results Discussion Chapter 8 The effectiveness of a habitat classification scheme as a surrogate for offshore fish biodiversity in a marine protected area Introduction Methods Results Discussion Chapter 9 General Discussion and Conclusion Appendices Page v

6 References Page vi

7 List of Figures Figure 3.1: Port Stephens-Great Lakes Marine Park extends from Cape Hawke Surf Life Saving Club near Forster south to Birubi Beach Life Saving Club near Anna Bay Figure 3.2: Port Stephens-Great Lakes Marine Park habitat map (New South Wales Marine Park Authority, 2006) Figure 3.3: Port Stephens-Great Lakes Marine Park zoning plan (New South Wales Marine Park Authority, 2007) Figure 4.1: Location of study sites in Port Stephens-Great Lakes Marine Park. Symbols represent offshore island locations (square) and coastal headland locations (circle) Figure 4.2: Changes in estimates of multivariate precision with increasing replication at a) Fingal and b) Broughton Island in sponge-dominated deep reef habitat in the Port Stephens- Great Lakes Marine Park. Values shown are mean precision ± standard error (n = 5) for datasets based on 5, 10, 15, 20, 25 and 30 replicate images. Symbols represent datasets calculated utilising 25, 50 and 100 grid-point matrices Figure 4.3: Life form accumulation curves from Fingal and Broughton Island for increasing sampling effort (number of images) and image processing (number of grid points) for sessile assemblages in intermediate reef habitat in the Port Stephens-Great Lakes Marine Park. Values shown are number of species recorded vs number of images. Symbols represent datasets calculated utilising 5, 10, 15, 20, 25 and 30 images Figure 4.4: Mean lifeform richness and mean cover of variables recorded from sessile benthic assemblages in December Values shown are mean cover ± standard error (n = 25) for each location. FI: Fingal, Br: Broughton Island Figure 4.5: nmds ordination plot (based on average cover of life forms at each location) depicting relative similarity of sessile assemblages of intermediate reef in the Port Stephens- Great Lakes Marine Park from offshore islands (square) and coastal headlands (circle) Figure 4.6: nmds ordination plot (based on average cover of life forms at each location) depicting relative similarity of sessile assemblages identified into broad taxonomic groups in intermediate reef in the Port Stephens-Great Lakes Marine Park from offshore islands (square) and coastal headlands (circle) Page vii

8 Figure 4.7: nmds ordination plot (based on average cover of life forms at each location) depicting relative similarity of sponge life forms of intermediate reef in the Port Stephens- Great Lakes Marine Park from offshore islands (square) and coastal headlands (circle) Figure 5.1: Location of study sites in Port Stephens-Great Lakes Marine Park. Symbols represent offshore island (square) and coastal headland (circle) Figure 5.2: Rank-correlograms produced for each location by correlation of Bray Curtis dissimilarity between samples separated by increasing distance class. indicates a significant negative result (correlation significant at p>0.975); indicates significant positive result (correlation significant at p<0.025) Figure 5.3 (continued): Rank-correlograms produced for each location by correlation of Bray Curtis dissimilarity between samples separated by increasing distance class. indicates a significant negative result (correlation significant at p>0.975); indicates significant positive result (correlation significant at p<0.025) Figure 5.4: Rank-correlograms for benthic assemblages produced for coastal headland and offshore island environmental domain by correlation of Bray Curtis dissimilarity between samples separated by distance class in PSGLMP. indicates a significant negative result (p > 0.975); indicates significant positive result (p < 0.025) Figure 5.5: Rank-correlograms for sponge assemblage data produced for coastal headland and offshore island environmental domain by correlation of Bray Curtis dissimilarity between samples separated by distance class in PSGLMP. indicates a significant negative result (p > 0.975); indicates significant positive result (p < 0.025) Figure 5.6: Rank-correlograms for benthic assemblage data over similar spatial scales, produced for coastal headland and offshore island environmental domain by correlation of Bray Curtis dissimilarity between samples separated by distance class in PSGLMP. indicates a significant negative result (p > 0.975); indicates significant positive result (p < 0.025) Figure 5.7: Rank-correlograms for sponge assemblages over similar spatial scales, produced for coastal headland and offshore island environmental domain by correlation of Bray Curtis dissimilarity between samples separated by distance class in PSGLMP. indicates a significant negative result (p > 0.975); indicates significant positive result (p < 0.025) Page viii

9 Figure 6.1: Location of study sites in Port Stephens-Great Lakes Marine Park. Symbols represent offshore island (triangle), coastal headland (square), and within Port Stephens estuary (circle) Figure 6.2: nmds ordination plots (based on MaxN of each species) depicting similarity in fish assemblages of sponge-dominated reef habitat in the Port Stephens-Great Lakes Marine Park in September 2009 (left) and 2010 (right). Symbols represent offshore islands (open symbols- Broughton Island = triangle, Cabbage Tree Island = square, Boondalbah Island = diamond), coastal headlands (Fingal = square) and within the Port Stephens estuary (litte beach, halifax park and fly point = circle) Figure 6.3: nmds ordination plots (based on MaxN of each species) depicting similarity in fish assemblages of sponge-dominated reef habitat in 2009 (open symbols) and 2010 (filled symbols) in the Port Stephens-Great Lakes Marine Park. Symbols represent offshore islands (triangle), coastal headlands (square) and within the Port Stephens estuary (circle) Figure 6.4: MaxN of fishes in sponge-dominated subtidal rocky reef habitat in 2009 (dark) and 2010 (light). Values shown are mean MaxN (+SE) at each domain Figure 7.1: Location of study sites in Port Stephens-Great Lakes Marine Park. Symbols represent offshore island (square) and coastal headland (circle) Figure 7.2: Unconstrained PCO plot of the spatial structure of fish assemblages sampled on subtidal reefs in the Port Stephens-Great Lakes Marine Park (solid symbols represent headlands, hollow symbols represent islands). The vector overlays represent species with a Pearson correlation of at least 0.65 with the PCO axes Figure 7.3: dbrda ordination plot showing the spatial structure of fish assemblages sampled on subtidal reefs in the Port Stephens-Great Lakes Marine Park (solid symbols represent headlands, hollow symbols represent islands) overlaid with the vectors of the environmental variable that explained a significant amount of variation in the assemblages. The vector represents the direction and magnitude of the Pearson correlation of the variable with the dbrda axes Figure 8.1: Location of study sites in Port Stephens-Great Lakes Marine Park. Pairs of symbols represent locations and different depths (empty symbol: shallow; filled symbol: intermediate depth) Page ix

10 Figure 8.2: nmds ordination plots (based on site-average MaxN of each species) depicting similarity in fish assemblages of offshore unvegetated unconsolidated habitats from shallow (filled symbols; estuary is a circle) and intermediate (unfilled symbols) depths in the Port Stephens-Great Lakes Marine Park in March (left) and September (right) Symbols represent 4 locations within each depth, and 2 sites within each location Figure 8.3: MaxN and species richness of fishes in shallow and intermediate habitat in March and September Values shown are mean MaxN ± standard error (n=4) for each replicate site at each location. SL: Shallow Location, IL: Intermediate Location, S1: Site 1, S2: Site 2. Colours represent two sample periods within each habitat Page x

11 List of Tables Table 4.1: Summary of results of 2-factor PERMANOVA testing for the influence of environmental domains on sessile benthic categories in sponge dominated reef in the Port Stephens-Great Lakes Marine Park Table 4.2: Summary of results of 2-factor PERMANOVA testing for the influence of environmental domain on sessile benthic assemblages, assemblages identified into broad taxonomic groups and sponge life form groups in sponge dominated reef in the Port Stephens-Great Lakes Marine Park Table 4.3: Overall dissimilarity (i ) of sponge life forms between offshore island and coastal headland locations (SIMPER). Species regarded as being important contributors to the assemblage dissimilarity are shown in bold. Values shown in the pairwise comparisons are the average percent cover for the life form Table 5.1: Mean % cover (±SE) of the major groups of organisms and two substrate variables in sessile benthic assemblages of subtidal rocky reefs in the Port Stephens-Great Lakes Marine Park Table 5.2: Spearman s rank correlation coefficients (Rho) between biological dissimilarity and distance of images from a single 25 m transect in each location, and a subset of data (sponge morphological groups) of subtidal rocky reef in the Port Stephens-Great Lakes Marine Park Table 5.3: Spearman s correlation coefficients (Rho) between biological dissimilarity and distance between all transects in offshore island and coastal headland environmental domains, and a subset of data (sponge morphological groups) for subtidal rocky reef in the Port Stephens-Great Lakes Marine Park Table 6.1: Summary of results of 2-factor PERMANOVA testing for the influence of time and environmental domains (with depth as covariate) on fish assemblages of subtidal reef habitat in the Port Stephens-Great Lakes Marine Park Table 6.2: Summary of results of SIMPER analysis showing the contributions of individual fish species to dissimilarity of assemblages of each environmental domain, and each time within the coastal headland domain. Species regarded as being important contributors to the assemblage dissimilarity are shown in bold (see Methods). Values shown in the pairwise Page xi

12 comparisons are the average MaxN for the species, i is the average contribution of the ith species to the overall dissimilarity ( ) between two groups, and SD is standard deviation Table 6.3: Summary of results of 2-factor PERMANOVA testing for the influence of time and environmental domains on total MaxN, MaxN of abundant species and species richness of fishes in sponge dominated reef habitat in the Port Stephens-Great Lakes Marine Park. 112 Table 7.1: Mean % cover (±SE) of the major groups of organisms and two substrate variables recorded in sponge-domianted rocky reef habitat in the Port Stephens-Great Lakes Marine Park Table 7.2: Correlation between fish and sessile benthic assemblages, and fish assemblages and habitat biological diversity (RELATE).Values shown are Spearman rank correlation coefficients (ρ) and their P-values for the entire fish assemblage and reef-associated fish assemblage Table 7.3: Results of marginal tests in a DISTLM analysis showing the proportion of variation in spatial variation of fish assemblages explained by each of the habitat attributes. Environment is a categorical variable (headland, island) Table 7.4: Results of marginal tests in a DISTLM analysis showing the proportion of variation in spatial variation of species richness and total MaxN independently explained by each of the habitat attributes. Environment is a categorical variable (headland, island) Table 7.5: Results of DISTLM analysis (based on step-wise selection and adjusted R 2, n=9999 permutations) showing the proportion of spatial variation in total MaxN of fishes that is significantly explained by the selected habitat attributes. Addition of further habitat attributes did not add a significant amount to the proportion of explained variation Table 7.6: Habitat biological diversity values (Shannon-Wiener diversity index H ) Table 7.7: Summary of results of DISTLM test for the relationship between the Shannon- Weiner biological diversity of the habitat, and attributes of the fish assemblage. MaxN data for the total fish assemblage and the reef-associated fish assemblage were square-root transformed prior to analysis Page xii

13 Table 8.1: Summary of results of 4-factor PERMANOVA testing for the influence of time, habitat (shallow, intermediate depth), locations (habitat) and sites (locations(habitat)) on fish assemblages of the Port Stephens-Great Lakes Marine Park Table 8.2: Overall dissimilarity ( i) in fish assemblages between habitats (SIMPER). Species regarded as being important contributors to the assemblage dissimilarity are shown in bold. Values shown in the pairwise comparisons are the average MaxN for the species Table 8.3: Summary of results of four factor ANOVA testing for the influence of time, habitat (shallow, intermediate depth), locations (habitat) and sites (locations(habitat)) on fish assemblages of the Port Stephens-Great Lakes Marine Park Page xiii

14 Abstract The effectiveness of marine protected areas (MPAs) in conserving biodiversity depends, in part, on which areas are chosen for protection and how these areas represent the true biodiversity of the planning region. Advances in acoustic technology have enabled high resolution maps of seabed habitats to create habitat maps based on depth and sea bed characteristics, which is quicker and cheaper than sampling biota over similar spatial extents. These habitat classification schemes are often used as surrogates of biodiversity for fish and benthic assemblages in the absence of biodiversity inventories, to depict spatial variation in biodiversity and support conservation planning. However, the intra-habitat variability and precision of these biodiversity surrogates is largely unknown. The aim of this thesis is to assess the effectiveness of habitat classification schemes as surrogates for biodiversity conservation in Port Stephens-Great Lakes Marine Park (PSGLMP). Fishes were sampled with baited remote underwater video stations (BRUVS) and sessile benthic assemblages were surveyed using an Autonomous Underwater Vehicle (AUV). The results of this study indicate that habitat mapping based on depth is a suitable surrogate for biodiversity of fish assemblages in unvegetated, unconsolidated habitats. Habitat mapping based on depth only categories is not a suitable surrogate for biodiversity of rocky reef sessile benthic assemblages, nor fish assemblages in sponge-dominated reef habitat. Multiple samples of sessile benthic assemblages and fish assemblages from a range of locations subject to differing environmental influences are required to adequately conserve representative samples of biodiversity within the PSGLMP. In the context of MPA planning, sessile benthic assemblages are not a suitable surrogate for biodiversity of fish assemblages. An examination of scales of autocorrelation in sessile benthic assemblages indicates a significant positive correlation between distance and dissimilarity, meaning that assemblages become more dissimilar as distance increases. Biodiversity sampling in this habitat is required at a fine scale (25 m) for the purposes of creating habitat maps for MPA planning. The results of this study have important consequences for future MPA planning, indicating that representative samples of rocky reef fish and sessile benthic assemblages from a variety of locations within differing environmental domains are required to adequately conserve representative samples of biodiversity. More studies are required to effectively understand what additional information needs to be incorporated into habitat classification schemes so Page xiv

15 that they can act as a surrogate for biodiversity for the range of assemblages conserved within PSGLMP. Page xv

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